A SIMPLE LC/MS/MS METHOD TO DETERMINE RELATIVE …dmd.aspetjournals.org/content/dmd/early/2010/09/16/... · 9/16/2010 · characterized authentic standards of metabolites for use

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A SIMPLE LC/MS/MS METHOD TO DETERMINE RELATIVE PLASMA

EXPOSURES OF DRUG METABOLITES ACROSS SPECIES FOR

METABOLITE SAFETY ASSESSMENTS (MIST)

Hongying Gao, Shibing Deng, and R. Scott Obach

Pharmacokinetics, Dynamics and Metabolism (HY. G., R. S. O.), Biostatistics (SB. D.) , Pfizer Inc,

Groton, CT

DMD Fast Forward. Published on September 16, 2010 as doi:10.1124/dmd.110.034637

Copyright 2010 by the American Society for Pharmacology and Experimental Therapeutics.

This article has not been copyedited and formatted. The final version may differ from this version.DMD Fast Forward. Published on September 16, 2010 as DOI: 10.1124/dmd.110.034637

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Running title: Direct and Quantitative Evaluation of MIST Coverage Using LC-MSMS

Corresponding author: Hongying Gao

Pharmacokinetics, Dynamics and Metabolism, Pfizer, Inc., Groton, CT 06340

Tel: 860-715-2432

Email: [email protected]

Text Pages: 21

Tables: 2

Figures: 7

References: 23

Abstract: 250

Introduction: 784

Discussions: 1564


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ABSTRACT

Recent regulatory guidance suggests that metabolites identified in human plasma should be

present at equal or greater levels in one of the animal species used in safety assessments. In this

report, an HPLC-MS/MS method is described whereby quantitative comparisons of exposures to

metabolites between species can be obtained in the absence of authentic standards of the

metabolites, calibration curves, and other attributes of standard bioanalytical methods. This

novel method was tested using six drug/metabolites combinations. Plasma samples from animal

are mixed with control plasma from human, and vice-versa, to remove possible differential

effects of matrices. Through multiple ion monitoring triggered enhanced product ion (EPI)

scans, all metabolites were qualitatively confirmed and daughter ions were selected for the most

sensitive mass transitions to trigger EPI scans. Direct comparisons of metabolites in animal vs.

human plasma were achieved by calculating the peak area ratios of the metabolites vs. internal

standard. Linearity of instrument responses was established by serial dilution. A statistical

analysis demonstrated that experimentally measured ratios of the parent and metabolites in rat vs.

human correlated well with the nominal ratios of concentrations using linear regression with an

average slope of 0.99±0.08 (r: 0.994±0.005). This analysis showed that if the experimentally

determined ratio of mass spectrometer responses is ≥2.0 then the actual exposure ratio is unity or

greater (p<0.01). This method offers time and resource-sparing advantages to ascertaining

metabolite exposure comparisons between humans and laboratory animal species. A strategy for

application of this approach within standard drug development processes is described.


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INTRODUCTION

The use of laboratory animal species to predict the safety of new drug candidates is based

on the condition that the animals have been safely exposed to the new compound at multiple

exposure to which humans will be subjected under ordinary therapeutic application. Recently,

this strategy has been extended to include exposure to circulating metabolites of the new

compound, since it is possible that toxicity could be effected by metabolites. Perspectives on the

topic of drug metabolites and their relevance in safety testing, commonly known as “MIST,” or

Metabolites in Safety Testing, have been offered (Baillie, et al., 2002; Hastings, et al., 2003;

Smith and Obach, 2005, 2006, 2009; Humphreys and Unger, 2006; Bruno-Davis and Atrakchi,

2006; Atrakchi, 2009; Robison and Jacobs, 2010).

The U.S. Food and Drug Administration and the International Conference on

Harmonization have issued guidances defining expectations regarding the demonstration of the

exposure of laboratory animals to human drug metabolites, and how studies should proceed to

evaluate human safety in the event that adequate exposure to human metabolites in the

toxicological species is not attained through administration of the parent drug.

(http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/u

cm079266.pdf, http://www.ich.org/LOB/media/MEDIA5544.pdf). In general, for those

metabolites that exceed a defined threshold in humans (i.e. 10% of total drug-related material, or

10% of the exposure to parent drug in plasma, in the ICH and FDA guidances, respectively), it is

required that at least one animal species demonstrates equal or greater steady-state exposure to

the metabolite than humans. If this is not achieved, then additional toxicology studies, or an

alternate toxicological species must be chosen to achieve the recommended exposure to the

metabolite(s). While it is possible that adequate exposure to metabolites will not be achieved in


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safety studies, it is more frequently the case that animals are exposed to greater concentrations of

human drug metabolites, even if these metabolic pathways are relatively minor in animals (Smith

and Obach, 2006). This is likely due to the fact that the doses of parent compound administered

to animals in toxicology studies far exceeds the pharmacologically active doses given to humans,

when corrected for relative body weight.

The measurement of steady-state plasma concentrations of drug metabolites in animals

and humans can be complex, and resource intensive. The preparation of adequate quantities of

characterized authentic standards of metabolites for use in assay development, validation, and

analysis can be challenging, and sometimes impossible. Furthermore, developing a rigorous

quantitative bioanalytical assay(s) for multiple analytes (i.e. drug + metabolites) can require

considerable effort (Unger and Humphreys, 2006). Nevertheless, many drug candidates generate

multiple metabolites in human that exceed the recommended relative thresholds defined by

regulatory agencies (e.g. 10% of the total drug related material) and therefore require this

investment. There have been approaches described which offer an ability to measure drug

metabolites without the synthesis of an authentic standard. These have included the generation

of a radio-labeled calibration standard of metabolite from a biological source (Zhang, et al.,

2007; Leclercq, et al, 2009 ) or establishing a stock solution concentration of metabolite that has

been isolated by using 1H-NMR and using that solution for the construction of standard curves

(Vishwanathan, et al., 2009). It has been proposed that LC/MS/MS peak areas can be used as

relative concentration comparison between animals and human to demonstrate the coverage of

metabolites exposure in animals, and some bioanalytical issues have been discussed and remain

to be resolved (Walker, et al, 2009; Leclercq, et al, 2009).


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The hybrid quadrupole linear ion trap mass spectrometer (QTRAP) has been used to

quantitate the parent drug and simultaneously screen metabolites in biological matrix (Xia, et al,

2003; Li, et al, 2005). Multiple ion monitoring (MIM) can be used to trigger an enhanced

product ion scan (EPI) to identify a large number of metabolites in a single chromatographic run

(Yao, et al, 2008). Similarly multiple ion monitoring (MRM) can be employed to trigger EPI

scans to profile predicted drug metabolites in in vitro samples (Shou, et al., 2005; Gao, et al,

2007).

In this report, we describe the use of these mass spectrometric capabilities along with a

previously described algorithm for MIST (Walker, et al., 2009) to produce a resource-sparing

strategy for the confident determination of the relative metabolite plasma exposures between the

toxicological species and human. This strategy is based on the notion that it is unnecessary to

make actual determinations of plasma concentrations of metabolites in animals and humans, but

that it is only necessary to demonstrate that animals have greater exposures relative to humans.

The experimental approach using LC/MS/MS peak area ratios to determine if one species has a

greater exposure to a metabolite is described herein using six drugs and their metabolites, along

with a statistical analysis that demonstrates its utility and limits.


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MATERIALS AND METHODS

Chemicals and Reagents

HPLC grade water was purchased from J. T. Baker (Phillipsburg, NJ, USA). ACS

reagent grade acetonitrile was purchased from Honeywell Burdick & Jackson (Muskegon, MI,

USA). Formic acid, diclofenac, zidovidine (AZT), dextrorphan, dextromethorphan, terfenadine,

and tacrine were purchased from Sigma/Aldrich (St. Louis, MO, USA). Fexofenadine was

purchased from Sequoia (Oxford, UK). Hydroxytacrine isomers, ziprasidone, and its metabolites

were obtained from Pfizer Inc. (Groton, CT). 3-Methoxymorphinan was purchased from

Research Biochemicals Inc (Natick, MA). 5-Hydroxydiclofenac was purchased from Toronto

Research Chemicals (Toronto, ON, Canada). AZT-glucuronide and 4’-hydroxydiclofenac were

prepared by Cerilliant Inc. (Austin, TX, USA). Wistar Hanover rat and human K3EDTA plasma

were purchased from Bioreclamation, Inc. (Westbury, NY, USA).

Sample preparation

To evaluate the strategy and to mimic the types of samples one would analyze with this

approach, a set of a drug and its metabolites were spiked into Wistar Hanover rat and human

plasmas. This was done for six drug/metabolite combinations and each combination was spiked

in rat or human plasma to generate 4 different sample sets to cover the range of ratios that may

be produced in actual samples. (The concentrations of individual analytes are listed in the

Supplemental Information). Six replicates of the ziprasidone combination were prepared to

access the inter-day assay variability of the strategy. The samples and the molecular weights of

the drugs and metabolites were provided to the bioanalytical chemist but they were blinded to the

spiked metabolite concentrations.


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In order to achieve a consistent matrix composition across all of the samples, plasma

samples were diluted 1:1 with plasma of the opposite species to yield a 2-fold dilution of the

samples. One sample set from each drug/metabolites combination was then serially diluted with

1:1 rat:human blank plasma to maintain the composition of the matrix and yield 5, 10, 20, 50,

and 100-fold diluted samples. All samples were then prepared for LC/MS/MS analysis by the

addition of 4 volumes of 100 ng/mL sulfadimethoxine in acetonitrile as an internal standard (IS)

and protein precipitation reagent except for the AZT/AZT-glucuronide plasma samples where

0.1% formic acid was added to the IS solution to stabilize the glucuronide conjugate. Samples

were centrifuged and the supernatants were dried under nitrogen and reconstituted with 20 µL of

acetonitrile with 0.1% formic acid followed by 180 µL of water with 0.1% formic acid for

sample analysis.

Liquid Chromatographic and Mass Spectrometric Methods

All sample analysis was carried out on an API-4000 QTRAP™ triple quadrupole-linear

ion trap mass spectrometer equipped with a Turbo V Ionspray ionization source and all

instrumentation control and quantitation was through the mass spectrometer AnalystTM software

package (Applied Biosystems, Foster City, CA, USA). The HPLC system consisted of two

Shimadzu Prominence LC-AD20 components (Columbia, MD, USA). The autosampler was a

CTC Analytics PAL autosampler (CTC Analytics AG, Zwingen, Switzerland).

Chromatographic separation was accomplished on a Phenomenex Kinetex C18 column (2.6µm,

150×4.6 mm, Phenomenex USA, Torrance, CA). The mobile phase consisted of two solvents,

solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in acetonitrile). The

following linear gradient was applied as a default gradient for all drug/metabolite combinations:

0 to 3 min, 2%B (modified to 20%B for diclofenac samples); 3 to 33 min, 2% to 80%B


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(modified to 20% to 70%B for diclofenac samples); 33 to 36 min, 80% B (modified to 70%B for

diclofenac) to 98%B; 38 to 41 min, 98 to 2%B, 41 to 45 min, 2%B. The flow rate was 0.5

mL/min. The total run time for each injection was 45 minutes. A Valco VICI valve (Valco

Instruments Co., Houston, TX) was used to divert the first 0.5 min and the last 7 minutes of

HPLC effluent to waste. The injection volume was 10 µL.

For each analyte/metabolite combination, the analyte ionization parameters were

optimized by infusing solutions of the parent drugs and internal standard in 50:50 0.1% formic

acid in water:acetonitrile. Ionization and mass dependent parameters for the parent drugs were

used for their metabolites except for the AZT-glucuronide conjugate where the declustering

potential (DP) was lowered to 50 V and the source temperature was lowered to 350°C. The

internal standard was monitored at the MRM transition of m/z 311> m/z 156 in positive ion mode

and m/z 309 > m/z 122 in negative ion mode.

An information dependent acquisition (IDA) method was employed to trigger the

collection of enhanced product ion scans for method development and qualitative identification

of the metabolites. The first experiment of the mass spectrometer was set in the MIM or MRM

mode for the parent/metabolite combinations. Detection of an ion signal greater than 5000 cps

then triggered collisionally activated enhanced product ion (EPI) scans to generate structurally

specific dissociation of the ion. EPI spectra were collected for three consecutive scans followed

by an EPI scan mode exclusion time of 1 second. The parent ion for the IS was listed in the IDA

exclusion list across the full LC run. The EPI scan was operated at a scan rate of 4000 amu/s

using the dynamic fill option in the linear ion trap. The collision energy was set at 40 eV (-20

eV for diclofenac) with a spread of 30 eV. The dwell time for each MIM/MRM transition was

50ms and the total cycle time was approximately 0.7 s.


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MIM_EPI: Qualitative Identification of Metabolites. In the execution of this

strategy, a list of the metabolite molecular ions, some fragmentation information, and HPLC

behavior will be known from preliminary metabolite scouting studies and can be provided as

input information to the bioanalytical scientist. The list of metabolites can be selected as ≥10%

of total parent related material based on the radio-labeled ADME study, or the estimation from

LC-UV-MS responses from a multiple dose human study. In the latter case, the accuracy of the

percentage of the total parent related materials is not critical, rather, the list of metabolites

should be comprehensive to cover all metabolites suspected to be important since the mass

spectrometric method has capability to simultaneously monitor fifty mass transitions (Gao, et al,

2007). The list of metabolites should be generated in during routine metabolite identification

studies and transferred to bioanalytical scientist. It will then be necessary for the bioanalyst to

qualitatively confirm that the ions being quantitated are indeed the targeted metabolites.

Qualitative confirmation that the targeted metabolites have been identified in both animal and

human plasma is achieved to inject the 2-fold diluted samples to LC/MS/MS system using the

MIM_EPI scan mode of the instrument. During the MIM mode of the experiment, the

metabolite parent ions were selected in the first and third quadrupoles with the collision cell (Q2)

set at a minimal collision energy of 5 eV. Once sufficient ion counts were detected the linear

trap (Q3) of the instrument switched to the EPI mode triggering the fragmentation and detection

of the resulting daughter ions. The resulting characteristic “fingerprint” fragmentation pattern of

the metabolite provides the qualitative confirmation of the metabolite.

MRM_EPI and Quantitation of the Targeted Metabolites: Assay sensitivity,

selectivity from chemical noise, and quantitation were achieved by chromatographic peak

quantitation in the MRM mode of the instrument using a second chromatographic injection. For


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each metabolite quantitated, Q1 was set at the parent ion of the metabolite and Q3 was set to

monitor one or more selected daughter ions that were observed for the metabolite in the

MIM_EPI scan. The MRM transitions for the parent drug and the collision energy for the

metabolites were determined from the authentic drug standard except when knowledge of a

putative metabolite warranted a lower collision energy. For example, the collision energy would

be scaled to lower values (e.g. 30 eV) for small molecules that are dealkylated (e.g. M1, M2, and

M5 of ziprasidone). Similar to the prior experiment, the detection of sufficient ion counts

triggers EPI scans so that at all times during the experiment there is qualitative confirmation that

the targeted metabolite is being quantitated.

Chromatographic peaks were integrated and peak area ratios of metabolites vs. internal

standard at the MRM transitions were calculated. Direct comparisons of metabolites in rat vs.

human plasma were achieved by calculating the rat:human ratio of these peak area ratios.

Statistical Methods

The statistical validity and limits of the strategy were determined from each data set. The

rat to human concentration ratio was calculated in a pair-wise fashion for each drug and

metabolite for both the experimentally determined mass spectrometric values and the known

nominal concentration values. The ratios were log transformed prior to analysis to stabilize the

variability across the range of the ratios. The differences between log transformed rat:human

experimentally determined mass spectrometric ratios and the actual nominal ratios were

calculated for all drugs and metabolites as well as their 95% confidence intervals (CIs). These

differences and CIs were anti-log transformed back to obtain the experimentally measured mass

spectrometric ratio: nominal ratios of actual concentration values and their 95% CIs. The 95%


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CIs were used to assess the equivalence of the two methods in determining the rat-to-human

ratio. The absolute difference between log transformed MS and nominal ratios were calculated

for all drugs and metabolites to obtain the geometric average of the fold change between the two

methods, as well as their upper 95% and 99% prediction confidence limits. The analysis was

performed for both the replicated ziprasidone experiments and the multiple drug experiments.

All data were analyzed in R version 2.9.1. (www.r-project.org).


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RESULTS

Daughter ion selection All target metabolites for the six combinations of parent

drugs and their metabolites were found and spectra were used to compare to the parent for

structural confirmation. The compounds and their metabolites used for this analysis (Figure 1)

were selected to present various challenges to the strategy, such as multiple structural isomers

(e.g. tacrine, diclofenac, and dextromethorphan metabolites), metabolites wherein major portions

are removed (e.g. ziprasidone), phase 2 metabolites (AZT), and metabolites in which substantial

changes in pKa are introduced (e.g. terfenadine, AZT). MRM transitions for the six

combinations of parent drug/metabolites are listed in Table 1. The total ion chromatogram and

the EPI spectra of ziprasidone and its 5 metabolites are shown as an example in Figure 2a-f.

The necessity for both the MIM_EPI and MRM_EPI runs for the qualitative confirmation

and quantitation of the targeted metabolite is illustrated in these spectra. For example, the

oxidative metabolite (M10) of ziprasidone produces a similar fragmentation to the parent with

some daughter ions common to both (e.g. m/z, 194, 159). In this case one can predict the MRM

transitions for quantitation without the MIM_EPI experiment. However, some metabolites

produce fragmentation patterns very different from the parent such as the N-dealkylated

metabolite (M5) and the oxidized N-dealkylated metabolites (M1, M2) of ziprasidone. In these

cases the MRM transitions cannot be predicted from the parent fragmentation and the MIM_EPI

scan is required for assay development. In these experiments, we observed that the MIM_EPI

scan mode produced sufficient product ions for the unambiguous confirmation of the targeted

metabolites, and therefore should be used as a method development tool to select the MRM

transitions for semi-quantitation of the metabolites. In the absence of authentic standards, we


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determined that multiple daughter ions for the same metabolite should be monitored with EPI

scans to optimize the assay sensitivity and to ensure that the peak quantitated has been

qualitatively confirmed as the targeted metabolite. This will be particularly important for the

analysis of unknown samples in complex biological matrices.

Separation of isomeric metabolites Although EPI scans can produce structurally

specific fragmentation patterns for the unambiguous identification of a metabolite, isomeric

metabolites can and often do produce the same fragmentation patterns and are thus

indistinguishable by mass spectrometry. 1-Hydroxytacrine, 2-hydroxytacrine and 4-

hydroxytacrine produced identical product ion scan spectra and major daughter ions of m/z 197,

and 182 (Table 1). Similarly, 4’-Hydroxydiclofenac and 5-hydroxydiclofenac produced identical

daughter ions at m/z 266, 230, 194, and 166. For these sample sets we found that the new shell

particle technology provided the highest separation efficiency while maintaining a low

chromatography system back pressure (Gritti et al, 2008). Adequate separation of five of the six

tested drug/metabolites combinations was achieved, using a single, long default gradient on a

Kinetex C18 column. The isomeric metabolites 1-hydroxytacrine, 2-hydroxytacrine and 4-

hydroxytacrine were baseline separated using the default gradient as shown in Supplemental

Figure 1. Only 4’-hydroxydiclofenac and 5-hydroxydiclofenac could not be separated with the

default gradient (Supplemental Figure 2a) but this separation was achieved (Supplemental Figure

2b) with minor modification of the gradient as described in the Methods section.

Matrix effect Matrix specific effects on ionization efficiency are a known and

significant concern in the development of quantitative LC/MS/MS assays (Little, et al, 2006;

Ismaiel, et al, 2008). Blank animal plasma was added to the human plasma samples and vice-


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versa to normalize (but not eliminate) matrix ionization effects. The validity of matrix mixing to

normalize matrices was confirmed in these experiments by monitoring the elution of

phospholipids with MRM transitions (daughter ion 184, Nouri and Wujcik, 2009) in blank

human (Figure 3a), rat (Figure 3b), and mixed plasma (Figure 3c). The long default

chromatographic gradient with the efficient particles produced a wide chromatographic window

between 3 and 26 minutes where no significant phospholipids elute. Most of the

parent/metabolites eluted between 3-26 minutes thus matrix effects are minimal. Nevertheless,

diclofenac and its metabolites co-eluted with the detected phospholipids. While the average of

the animal:human ratio of peak area ratios was not significantly affected, it was observed that the

measurement error was larger for this drug/metabolite combination.

Linearity of instrument response For this approach to provide sound cross-

species comparisons, linearity in instrument response needs to be demonstrated. In this

approach, the plasma sample itself represented the highest metabolite concentration that must fall

within the linear range. Therefore, the linear response range of the instrument for the metabolite

was defined by serial dilution of the plasma sample in the mixed blank plasma matrix and the

determination of the dilution at which linear response is lost. It is the least diluted sample that

falls in the linear range that is used for the calculation of the animal to human exposure ratio.

Demonstration of response linearity using this approach is illustrated in Figure 4a for the M1

metabolite of ziprasidone in rat plasma. In this example, the initial 2-fold dilution falls within

the linear response of the instrument and can be used to calculate the exposure ratio. In another

example, Figure 4b illustrates the non-linearity of response observed for the M9 metabolite of

ziprasidone in rat plasma. Here a 2-fold and even a 5-fold dilution of the sample resulted in non-


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linear response and it was not until a 10-fold dilution of the sample was done that the linear

range was defined and a peak area ratio was obtained for confident exposure comparison.

Ratio measurements and error Six inter-day replicate analysis (n=6) of ziprasidone

and its metabolites done over a 3-month period demonstrated an average inter-day assay

variability (%CV) of rat:human concentration ratio measurements of 26.3%. Further statistical

analysis of the six replicates using the geometric average fold change demonstrated that

determination of the animal:human ratio from a singlicate measurement of the samples required

a ratio ≥2.23 or ≥2.71 be measured to reach the 95% or 99% confidence levels, respectively, that

the actual nominal concentration of the metabolite in animal was equal to or greater than that in

human (Table 2). The ratio that established that the plasma concentration of animal:human is

equal or greater than unity decreased to ≥1.77 or ≥1.94 to meet the 95% or 99% confidence level,

respectively, when three replicate analysis were performed. Interestingly there was diminishing

return in the fold change of the confidence limits beyond three replicates as the needed ratio to

establish unity or greater animal:human exposure only slightly decreased to ratios of ≥1.63 and

≥1.74 to produce confidence limits of 95% and 99%, respectively when six replicate analysis

were used (Table 2).

The experimentally determined individual drug or metabolite, rat:human concentration

ratios using this method correlated well with the nominal rat:human concentration ratios with an

average correlation coefficient of 0.994 and standard deviation of 0.005 over a wide dynamic

range of ratios (0.01 to 200) as shown in Figure 5. The average slope of the regressions was 0.99

with a standard deviation of 0.082. The quality of the correlation between the experimentally

determined ratios vs. the actual ratios and a regression slope that was near unity, demonstrated


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that this strategy has yielded accurate individual measurements of the relative ratios of plasma

concentrations in rat vs. human without authentic metabolite standards.

Figure 6 shows the statistical analysis for all 20 analytes used for this evaluation,

covering a wide range of chemical space and isomeric metabolites. Here the experimentally

determined ratio value/the actual ratio value is plotted for singlicate (n=1) measurement per

sample. Unity indicates that the experimentally determined ratio is equal to the true ratio value.

Almost all data points fall over the range of 0.80-1.3. From this plot, statistical analysis of all 20

analytes using the geometric average fold change indicated that for a singlicate measurement

(n=1) there is 95% confidence that the exposure in rat is equal to or greater than human when the

determined ratio is ≥1.83 and this confidence increases to 99% when the determined ratio is

≥2.07 (Figure 6). One can use these ratios and confidence limits as a guide over the entire

chemical space of the dataset. An assay run in singlicate can provide meaningful data regarding

MIST coverage, especially if the ratio of animal/human is very high. If the ratio is below 2.0,

then it is recommended that three inter-day assays covering the storage time duration should be

performed to provide the measurement error and indication of stability of the samples. If still

below this value, it is possible that the actual ratio is below unity and that the metabolite requires

further characterization of safety.


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DISCUSSION

The regulatory guidances on human metabolites safety assessment emphasize providing

assurance that human drug metabolites were also present in animal species used in toxicology

studies of the parent drug. Only in rare instances this is not the case such that further

toxicological investigation of the metabolite itself is warranted. In most cases, animals will have

greater exposures to metabolites than humans (by virtue of the higher doses used in animal

toxicology studies relative to clinical doses). But in order to demonstrate this, a bioanalytical

method is needed for each human metabolite of interest. Generating and validating assays for

multiple metabolites can be a large resource burden and result in delays in drug development

(Unger and Humphreys, 2006). Since it is only necessary to demonstrate that animals have

greater exposure levels than human, but not how much greater, a fully validated GLP

bioanalytical method to quantitate the metabolite is excessive. In this report, we have described

an abbreviated but robust approach to demonstrate the relative animal:human exposures to a

metabolite.

In this methodology, it has been demonstrated that the animal vs. human concentration

ratios determined from LC/MS/MS analyte/IS peak area ratios can adequately demonstrate

whether the ratio of nominal concentrations in animal vs. human is greater than unity within an

acceptable error range. Importantly, this can be accomplished even in the absence of authentic

standards of the metabolites, biosynthesized metabolites, or standards generated using

radiometric or NMR calibration. In this strategy, the key bioanalytical mass spectrometric issues

encountered when using response ratios for metabolite exposure assessment have been addressed

and solutions are provided:


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(a) The matrix difference across species was eliminated by mixing animal plasma samples

with control human plasma and vice-versa;

(b) Quantitative methods using MRM transitions were developed using MIM_EPI scans in

the prepared unknown samples;

(c) EPI scans triggered by MRM and MIM transitions were employed to provide the

confirmation of metabolite identification in unknown samples;

(d). Linearity of the instrument response was tested and established using serial dilution of

the unknown samples in the mixed plasma matrix; and

(e) Selectivity for isomeric metabolites with similar mass spectra was further optimized

through chromatographic separation.

The hybrid quadrupole linear ion trap was selected for this methodology because it

maintains the wide dynamic range of triple quadrupole instruments and fast scanning capability

of linear trap instruments. MRM transitions themselves are not specific enough to determine

metabolites in unknown samples without synthetic standards. EPI scans are necessary to confirm

metabolite identification by comparing the spectra with product ion scans previously generated

from metabolite profiles using other instrumentation, e.g. LTQ, Q-TOF, or Orbitrap. The

scanning mode in quadrupole yields a poor duty cycle, thus typical triple-quadrupole mass

spectrometer is not adequate for using this strategy. Linear ion trap instruments have fast

scanning capability, but the dynamic range is narrow due to space charge effects in the trap, and

the low energy collisions produced by in-trap resonance excitation often require multiple stages

of fragmentation (MSn) to provide the same coverage of the fragments generated in the triple-

quadrupole instruments (Hager and Yves LeBlanc, 2003). The ideal mass spectrometer

characteristics for the execution of this strategy are a wide dynamic range, fast scanning


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capability, and high mass resolution for metabolite identification in unknown samples. Further

advances in mass spectrometry may simplify the method development and analysis described

here as well as increase the confidence level of the measurements.

The statistical analysis indicated the concentration ratios in animal vs. human

experimentally determined from the mass spectrometric peak area ratios correlated well with the

ratios of the actual concentrations of the analytes in animal vs. human. From these data, the

nominal concentration of the metabolites in animal plasma could be determined to be greater

than that in human with 95% or 99% confidence, if the animal to human ratio determined by this

methodology is ≥1.83 or ≥2.07, respectively, for singlicate measurement (n=1), and the

confidence level can be increased by averaging the results of additional independent

measurements. While the average ratio and error margins were improved by repeating the

analysis, increasing the number of measurements beyond three did not appreciably improve the

confidence limit. Pooling of the samples across pharmacokinetic/toxicokinetic sampling times

using a mathematical algorithm can be done to generate a single sample for each species that

reflects the exposure (Hamilton, et al., 1981; Hop, et al, 1998). Thus, ascertaining the metabolite

exposure ratio between laboratory animals and humans can be done by analyzing as few as three

samples (i.e. blank human+blank animal plasma as a control, pooled human plasma sample

diluted with blank animal plasma, and pooled animal sample diluted with blank human plasma).

Greater numbers of samples can be analyzed depending on the number of species and dose levels

as well as whether greater confidence in the data is desired by analysis of replicates. This

methodology can provide the animal:human concentration ratios for all selected metabolites in

one overnight batch analysis. In applying this methodology strategically to meet the needs of

MIST, a majority of metabolites will never require synthesis, assay development and validation,


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or direct administration to animals if the ratio of the mass spectrometric peak area ratio is higher

than the minimal ratio, e.g. ≥2.0 with 99% confidence. Instead, only a handful of metabolites

may need to be investigated further if their animal:human concentration ratio is less than unity.

This offers tremendous resource and time savings in drug development. However, one key

limitation of the method is that the stability of individual metabolites may not be fully

established. Nevertheless, replicate analysis of the sample covering storage duration could

indicate if an analyte has a stability issue, i.e. the ratio would change significantly upon assay

repetition. For metabolite types known to possess stability issues, (e.g. acyl glucuoronide

conjugates), stabilization of the metabolites in plasma samples should be undertaken when

samples are collected.

A schematic illustrating a strategy regarding how to utilize this bioanalytical approach in

drug development to address steady-state metabolite exposures in human vs. toxicology species

is shown in Figure 7. This approach is best applied to samples from multiple-dose studies such

that steady-state metabolite exposures are assessed. Undertaking this approach can be triggered

by two types of observations: (1) actual demonstration using radiometric methods that a

metabolite is present in human circulation at 10% or more of total drug-related material in a

single dose ADME study or (2) anticipation that a human metabolite will be present in

circulation at 10% of drug-related material. In the latter instance, such a prediction could be

attempted from in vitro metabolism data or from qualitative investigations of circulating

metabolite profiles in samples from phase 1 clinical studies, in which relative metabolite

abundances are estimated from peak intensities in HPLC-UV-MS chromatograms. The focus of

such an estimation should be to provide a comprehensive list of identified/predicted metabolites

with possible MIST implications, rather than attempting to generate an accurate estimate of


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percentage of drug-related material. However, it should be appreciated that estimates of which

human metabolites will comprise >10% of total circulating drug-related material from anything

other than studies using radiolabeled material may be sometimes incorrect. A major metabolite

could be overlooked, or a metabolite could be aggressively pursued only later to be demonstrated

as a minor metabolite when the radio-labeled human study is done.

When the animal:human ratio of LC/MS/MS peak area ratio for a given metabolite is

≥2.0 (if analyzed just once) then it is safe to conclude that the animal species has exposure to the

metabolite that is at least equal to or greater than human with a high confidence (99%). If the

initially determined ratio is below 2.0 (n=1), and the subsequent average ratio is still below 2.0

after 3 repetitive measurements (n=3), it is possible that the exposure in animals may be lower

than in human, and further investigation will be needed to measure the exposure values using a

standard bioanalytical approach. In this case, a quantitation method using a chemically or

biologically synthesized standard of the metabolite is likely needed. Should the human exposure

to the metabolite still exceed that of laboratory animal species used in safety testing, further work

is warranted to provide assurance of safety of the metabolite (Atrakchi, 2009; Frederick and

Obach, 2010). Then it is worthy to check if the metabolite is indeed ≥10% total drug related

material from the radio-labeled ADME study. If so, then an alternative species may be selected

for toxicology studies such that a greater exposure to the metabolite will be attained, or the

metabolite will be directly administrated to animals in a toxicology study. For these studies, a

validated GLP method will be needed to carry out the analysis of plasma samples to measure the

circulating concentrations in order to compare the toxicokinetics to the human pharmacokinetics

of the metabolite.


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In this report, we have described an abbreviated yet robust approach to demonstrate that

one species has had a greater exposure to a metabolite than another. Using six drugs and their

metabolites, it was statistically shown that a response ratio of 2.0 is enough to be able to

conclude that the actual concentration ratio is at least unity. The method does not require an

authentic standard of the metabolite(s) and uses only a few pooled plasma samples to provide the

data. Thus, it should offer a facile and inexpensive approach to provide data needed to support

the understanding of the safety of metabolites of new drugs.


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Acknowledgements

The authors would like to thank Christopher Holliman for his support and for his review and

valuable editing of the manuscript.


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Davis-Bruno, Karen L.; Atrakchi, Aisar. (2006) A Regulatory Perspective on Issues and

Approaches in Characterizing Human Metabolites. Chem. Res. Toxicol. 19(12): 1561-1563.

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Hager, James W. and Yves LeBlanc, J. C. (2003) Product ion scanning using a Q-q-Q linear ion

trap (Q TRAPTM) mass spectrometer. Rapid Commun. Mass Spectrom. 17:1056-1064

Hamilton, R.A, Garnett, W.R. and Kline, B.J. (1981) Mean Serum Level Determination by

Assay of a Single Pooled Sample. Clin. Pharmacol. Ther. 29:409-413

Hop, Cornelis E. C. A.; Wang, Zhen; Chen, Qing; Kwei, Gloria. (1998), Plasma-Pooling

Methods To Increase Throughput for in Vivo Pharmacokinetic Screening. J. Pharm. Sci.

87(7): 901-903

Humphreys, W. Griffith; Unger, Steve E.. (2006), Safety Assessment of Drug Metabolites:

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Ismaiel, Omnia; Halquist, Matthew; Elmamly, Magda; Shalaby, Abdalla; Karnes, H. Thomas.

(2008) Monitoring phospholipids for assessment of ion enhancement and ion suppression in ESI


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Figure Legend

Figure 1. Structures of drugs and metabolites

Figure 2. Total ion chromatogram, and EPI spectra of ziprasidone and its 5 metabolites in rat

plasma sample 1. a). Total ion chromatogram of ziprasidone and 5 metabolites, b). EPI spectra

of ziprasidone, c). EPI spectra of metabolites M1, M2, M5, M9, M10.

Figure 3. Endogenous phospholipids in blank plasmas. a). Human plasma, b) Rat plasma, c).

Human+Rat plasma (1:1)

Figure 4. Serial dilution curve of ziprasidone metabolites in rat plasma sample 1. a). Metabolite

M1, b) M9

Figure 5. Correlation of rat:human ratio of mass spectrometric peak area ratio with nominal ratio

of actual spiked plasma concentrations in animal vs. human for individual analyte.

Figure 6. Error distribution of singlicate measurement of six drug/metabolite combinations

(n=1). The first measurement of Ziprasidone and its 5 metabolites was used. Geometric average

fold change was used for confidence level prediction.

FIGURE 7. A Schematic for Utilizing the Ratio Approach for Cross-Species Relative Metabolite

Exposures Assessments in Drug Development. The findings which could trigger this approach

are the observation of a metabolite that is 10% or more of the total drug-related material in

human plasma in the human radiolabel study or other data from which it can be reasonably

anticipated that a metabolite may be more than 10% of total in human. When this occurs, plasma

samples from humans and relevant toxicology species that have been dosed to steady-state are

acquired, and these samples are pooled such that a single sample per species is created in which

the parent drug and metabolite(s) will be present at Cavg. These samples are analyzed as

described in Methods. If the animal:human ratio of mass spectrometric peak area response,


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corrected for internal standard, exceeds 2.0, then no further analysis is needed as it can be

concluded that animals have a higher exposure than human. The investigator may decide to

replicate this analysis twice more to gain confidence in the conclusion. If less than 2.0, then

replicate analyses should be done and if the mean animal:human ratio is still less than 2.0,

investment in the development of a conventional bioanalytical approach is warranted to

determine the actual concentration values in individual plasma samples. Should this analysis

reveal that the animal:human steady-state exposure ratio is less than unity, more work will be

needed to provide assurance of the safety of the metabolite. This could include seeking an

alternate safety evaluation species that has greater exposure to the metabolite, or direct

administration of the metabolite to animals which will require a validated GLP method to

measure AUC for exposure comparison.


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Table 1. Drug/metabolites and their major daughter ions for MRM transitions

Drug/Metabolite Biotransformation Reaction(s) Q1 Q3 CE

Ziprasidone -- 413 194 43 M1 N-Dealkylation + S-Oxidation 236 134 30 M2 N-Dealkylation + S-Oxidation 252 209 30 M5 N-Dealkylation 220 177 30 M9 Reduction + S-Methylation 429 280†, 194 43 M10 S-Oxidation 429 194 43

Tacrine -- 199 171†, 144 45,53 1-Hydroxytacrine, 2-Hydroxytacrine, 4-Hydroxytacrine

Hydroxylation Hydroxylation Hydroxylation

215

197†, 182

30

Terfenadine -- 472 436†, 129 41, 59 Fexofenadine Hydroxylation + Oxidation 502 466†, 171 41, 59

Dextromorphan -- 272

215, 213 171†

30 57

Dextrophan O-Demethylation 258 201, 199† 30 3-Methoxymorphinan N-Demethylation 258 215†, 213, 30

Diclofenac 294 250 -18 4’-Hydroxydiclofenac 5-Hydroxydiclofenac

Hydroxylation Hydroxylation

310 266† -18 310 230, 194,

166 -30

Zidovudine (AZT) -- 268 127 17 AZT-Glu Glucuronidation 444 268, 127† 17

† Daughter ions were used in MRM transitions for peak area ratio measurements


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Table 2. Rat:human ratios determined from mass spectrometric peak area ratios with high

confidence that the nominal concentration ratio of rat vs. human ≥1

Metabolite

Measured MS ratio (when Nominal ratio=1)

MS ratio (n=6) (when Nominal

ratio≥1 )


ratio≥1)


ratio≥1)

p<0.05 p<0.01 p<0.05 p<0.01 p<0.05 p<0.01

M1 1.52 2.01 2.20 2.27 2.59 3.17 4.20

M2 1.32 1.54 1.62 1.65 1.77 1.98 2.31

M5 1.37 1.68 1.79 1.83 2.01 2.31 2.83

M9 1.22 1.39 1.44 1.46 1.55 1.70 1.92

M10 1.38 1.68 1.79 1.82 2.00 2.30 2.80

Ziprasidone 1.31 1.55 1.63 1.66 1.80 2.02 2.39

Average Ratio

1.34 1.63 1.74 1.77 1.94 2.23 2.71


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N

N

NH

S

N O

Cl

N

NS

O

NH

N

NSOO

N

NS

NN

N

O

Cl

NN

NS

N

NS

O

N

Cl

N

OZiprasidone M1 M2 M5

M9 M10

N

N

Tacrine

N

NH2 OH

1-hydroxytacrine

N

NH2OH

N

NH2

OH

2-hydroxytacrine 4-hydroxytacrine

O

N

O

Terfenadine

O

N

O

O

O

Fexofenadine

N

O

N

O

N N+

O

O

N

Zidovidine (AZT)

NN

+

N

ONN

O

O

OO

O

OO

O

O

AZT-Glu

N

OO

ClCl

Diclofenac

NH

OHO

ClCl

OH

NH

OHO

ClCl

OH

4’-hydroxydiclofenac 5-hydroxydiclofenac

N

O

H

CH3

N

OH

H

NHH

MeO

Dextromethorphan Dextrorphan 3-Methoxymorphinan

Figure 1

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atted. The final version m

ay differ from this version.

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a

b: ziprasidone

M1

M2

M5

M9

M10

Figure 2M9M10

Parent

M1

M2

M5




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Average:1.25

95% confidence : 1.83

99% confidence: 2.07

Figure 6




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Input Data:

a. Metabolite is observed in human plasma and is predicted to be >10% of total drug related material; or

b. Metabolite is observed in human radiolabel ADME study and is shown to be >10% of total drug-related material

Compare relative metabolite exposure ratio in human vs. animal using steady-state plasma samples pooled

across sampling times by HPLC-MS/MS analysis

Human dose = highest clinically relevant dose

Animal dose = NOAEL dose

Animal ≥ 2.0X HumanAnimal < 2.0X Human

Analyze Twice More

Animal ≥ 2.0X HumanAnimal <2.0X Human

Metabolite Safety Risk is Qualified by Virtue of Animal

Exposure

Invest in Generating Authentic Standard of the Metabolite and Developing a Quantitative Bioanalytical Method

Animal ≥1.0X HumanAnimal <1.0X Human

Metabolite ≥10% of total drug-related material in radio-labeled ADME study, Metabolite Safety

Risk Requires Qualification

Judgment: Run Replicates?

Metabolite <10% of total drug-related material in radio-

labeled ADME study, Metabolite Safety

Risk Assessment is not required

Find Alternative Species that generates it

Direct Test in Safety Studies and Develop a GLP BA Method to

Measure AUC in AnimalOR

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